What the data for this category looks like
Data for advertising and marketing funding daily reports comes primarily from industry monitoring platforms, public funding announcements, brand campaign ledgers, and third-party marketing data tools. Updates occur daily or every other day. Individual documents vary widely in length, from a few pages to dozens of pages. Most documents combine structured tables and paragraph descriptions. Core fields include advertising channel type, budget amount, conversion data, and ROI value. Common units include ten thousand yuan, thousand impressions, click counts, and similar metrics.
What constraints do these characteristics impose on document parsing and chunking?
Diverse data sources lead to inconsistent document formats. Files include native office documents and scanned formats, which requires adaptation for both OCR and native parsing. The daily update rhythm demands low-latency parsing processes to avoid delays that disrupt downstream steps. Wide document length variation and large numbers of structured tables—some with merged cells and cross-page content—require chunking that preserves table integrity and contextual connections. Parsing resource allocation must also adapt to documents of different sizes. The variety of units for core fields increases the difficulty of aligning data after chunking.
How to Configure Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
PARSE_FILE_TIMEOUT_SECONDS | 600-900 seconds | Individual advertising and marketing funding daily reports are typically 10-50 pages long. Standard parsing takes 300-800 seconds. This range adds buffer time to avoid timeouts |
UPLOAD_FILE_MAX_SIZE | 2000 MB | Some daily reports integrating multi-channel data may exceed 100 MB. This setting reserves sufficient space for large files |
maxChunkSize | 800-1200 characters | Documents contain long paragraph descriptions and structured tables. This range balances contextual completeness and chunk retrieval accuracy |
chunkOverlap | 100-150 characters | Cross-page tables and paragraphs require retained contextual connections to avoid lost associated information after chunking |
enable_table_parse | Enabled | Core document information is mostly concentrated in structured tables. Enabling this setting preserves table structure and field integrity |
ocr_mode | auto | Documents include a mix of native documents and scanned formats. Automatic mode adapts to parsing needs for different source types |
The parameter values provided on this page are common recommended starting points for configuration. Actual values are affected by material format, data volume, and business rules. Specific issues require individual analysis. Testing on local sample datasets is recommended prior to finalizing configuration values.
Three Common Mistakes
- Symptom: A
timeout of 360000ms exceedederror appears when uploading a funding daily report PDF larger than 10 MB. Cause: ThePARSE_FILE_TIMEOUT_SECONDSparameter was not adjusted. The default timeout duration is insufficient for parsing large, multi-table documents. - Symptom: Some docx-format funding daily reports cannot be parsed. Cause: The office document parsing engine was not enabled, or the document contains unrecognized embedded fonts or complex styling.
- Symptom: Uploaded funding daily report tables cannot be chunked correctly, with some field content split across multiple chunks. Cause: The
enable_table_parseconfiguration was not enabled, or themaxChunkSizevalue was too small, forcing table content to be split.
How to Verify Configurations Are Correct
- Upload a standard funding daily report with fewer than 50 pages. Check if the parsing task completes within a reasonable duration. Adjust
PARSE_FILE_TIMEOUT_SECONDSto match the actual time required. - Import a document containing tables with multiple merged cells. Verify that the parsed result retains full table structure and field correspondence. Confirm that
enable_table_parseis enabled. - Upload daily report documents in different formats (native docx, scanned PDF). Validate that text extraction from parsed results is complete. Confirm that the
ocr_modeconfiguration matches the document source type. - Review the chunked result list. Confirm that core fields are not overly split. Adjust
maxChunkSizeandchunkOverlapto values that fit the document structure.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-09-14.